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Modern chemistry makes possibile the production of artificial receptors endowed with interaction sites specific towards selected analytes. To fabricate chemical sensors a transducer able to preserve the selectivity of such sensing layers is requested. We demonstrate the Field Effect Transistors (FET) coated by metalloporphyrins emphasizes the coordination of analytes with the sensing molecules with respect to the weakest forces that tend to cancel the selectivity. Molecular simulations show that coordination of gases such as carbon monoxide and nitric oxide greatly change the porphyrin electric dipole both in magnitude and direction inducing a large FET signal shift.

This paper presents a 512-point feedforward FFT architecture for wireless personal area network (WPAN). The architecture processes a continuous flow of 8 samples in parallel, leading to a throughput of 2.64 GSamples/s. The FFT is computed in three stages that use radix-8 butterflies. This radix reduces significantly the number of rotators with respect to previous approaches based on radix-2. Besides, the proposed architecture uses the minimum memory that is required for a 512-point 8-parallel FFT. Experimental results show that besides its high throughput, the design is efficient in area and power consumption, improving the results of previous approaches. Specifically, for a wordlength of 16 bits, the proposed design consumes 61.5 mW and its area is 1.43 mm2.

This paper presents a 512-point feedforward FFT architecture for wireless personal area network (WPAN). The architecture processes a continuous flow of 8 samples in parallel, leading to a throughput of 2.64 GSamples/s. The FFT is computed in three stages that use radix-8 butterflies. This radix reduces significantly the number of rotators with respect to previous approaches based on radix-2. Besides, the proposed architecture uses the minimum memory that is required for a 512-point 8-parallel FFT. Experimental results show that besides its high throughput, the design is efficient in area and power consumption, improving the results of previous approaches. Specifically, for a wordlength of 16 bits, the proposed design consumes 61.5 mW and its area is 1.43 mm2.

This paper presents a 512-point feedforward FFT architecture for wireless personal area network (WPAN). The architecture processes a continuous flow of 8 samples in parallel, leading to a throughput of 2.64 GSamples/s. The FFT is computed in three stages that use radix-8 butterflies. This radix reduces significantly the number of rotators with respect to previous approaches based on radix-2. Besides, the proposed architecture uses the minimum memory that is required for a 512-point 8-parallel FFT. Experimental results show that besides its high throughput, the design is efficient in area and power consumption, improving the results of previous approaches. Specifically, for a wordlength of 16 bits, the proposed design consumes 61.5 mW and its area is 1.43 mm2.

This paper presents a 512-point feedforward FFT architecture for wireless personal area network (WPAN). The architecture processes a continuous flow of 8 samples in parallel, leading to a throughput of 2.64 GSamples/s. The FFT is computed in three stages that use radix-8 butterflies. This radix reduces significantly the number of rotators with respect to previous approaches based on radix-2. Besides, the proposed architecture uses the minimum memory that is required for a 512-point 8-parallel FFT. Experimental results show that besides its high throughput, the design is efficient in area and power consumption, improving the results of previous approaches. Specifically, for a wordlength of 16 bits, the proposed design consumes 61.5 mW and its area is 1.43 mm2.

This paper presents a 512-point feedforward FFT architecture for wireless personal area network (WPAN). The architecture processes a continuous flow of 8 samples in parallel, leading to a throughput of 2.64 GSamples/s. The FFT is computed in three stages that use radix-8 butterflies. This radix reduces significantly the number of rotators with respect to previous approaches based on radix-2. Besides, the proposed architecture uses the minimum memory that is required for a 512-point 8-parallel FFT. Experimental results show that besides its high throughput, the design is efficient in area and power consumption, improving the results of previous approaches. Specifically, for a wordlength of 16 bits, the proposed design consumes 61.5 mW and its area is 1.43 mm2.

The delay constraints imposed by future wirelessapplications require a suitable metric for assessing their impacton the overall system performance. Since the classical Shannon’s ergodic capacity fails to do so, the so-called effective rate was recently established as a rigorous alternative. Yet, most priorrelevant works have considered only the typical case of Rayleighfading which allows for tractable manipulations. In this paper,we relax this assumption by considering the more general Rician fading model for multiple-input single-output (MISO) systems. Anew, analytical expression for the exact effective rate is derived, along with tractable expressions for the key parameters dictating the effective rate performance in the high and low signal-to-noise(SNR) regimes.

The delay constraints imposed by future wirelessapplications require a suitable metric for assessing their impacton the overall system performance. Since the classical Shannon’s ergodic capacity fails to do so, the so-called effective rate was recently established as a rigorous alternative. Yet, most priorrelevant works have considered only the typical case of Rayleighfading which allows for tractable manipulations. In this paper,we relax this assumption by considering the more general Rician fading model for multiple-input single-output (MISO) systems. Anew, analytical expression for the exact effective rate is derived, along with tractable expressions for the key parameters dictating the effective rate performance in the high and low signal-to-noise(SNR) regimes.

The delay constraints imposed by future wirelessapplications require a suitable metric for assessing their impacton the overall system performance. Since the classical Shannon’s ergodic capacity fails to do so, the so-called effective rate was recently established as a rigorous alternative. Yet, most priorrelevant works have considered only the typical case of Rayleighfading which allows for tractable manipulations. In this paper,we relax this assumption by considering the more general Rician fading model for multiple-input single-output (MISO) systems. Anew, analytical expression for the exact effective rate is derived, along with tractable expressions for the key parameters dictating the effective rate performance in the high and low signal-to-noise(SNR) regimes.

The delay constraints imposed by future wirelessapplications require a suitable metric for assessing their impacton the overall system performance. Since the classical Shannon’s ergodic capacity fails to do so, the so-called effective rate was recently established as a rigorous alternative. Yet, most priorrelevant works have considered only the typical case of Rayleighfading which allows for tractable manipulations. In this paper,we relax this assumption by considering the more general Rician fading model for multiple-input single-output (MISO) systems. Anew, analytical expression for the exact effective rate is derived, along with tractable expressions for the key parameters dictating the effective rate performance in the high and low signal-to-noise(SNR) regimes.

The delay constraints imposed by future wirelessapplications require a suitable metric for assessing their impacton the overall system performance. Since the classical Shannon’s ergodic capacity fails to do so, the so-called effective rate was recently established as a rigorous alternative. Yet, most priorrelevant works have considered only the typical case of Rayleighfading which allows for tractable manipulations. In this paper,we relax this assumption by considering the more general Rician fading model for multiple-input single-output (MISO) systems. Anew, analytical expression for the exact effective rate is derived, along with tractable expressions for the key parameters dictating the effective rate performance in the high and low signal-to-noise(SNR) regimes.

In this study, we aim to estimate the unknown multi-modal measurement noise distribution of nonlinear state space models. The unknown noise distribution is modeled as a mixture of exponential family of distributions. We use the Expectation-Maximization (EM) method in order to jointly estimate the unknown parameters as well as the states. The online version of the EM algorithm is implemented by using particle filtering techniques. The resulting algorithm is a noise adaptive particle filter which is applicable to many sensor models having multi-modal noise distributions with unknown parameters.

In this study, we aim to estimate the unknown multi-modal measurement noise distribution of nonlinear state space models. The unknown noise distribution is modeled as a mixture of exponential family of distributions. We use the Expectation-Maximization (EM) method in order to jointly estimate the unknown parameters as well as the states. The online version of the EM algorithm is implemented by using particle filtering techniques. The resulting algorithm is a noise adaptive particle filter which is applicable to many sensor models having multi-modal noise distributions with unknown parameters.

In this study, we aim to estimate the unknown multi-modal measurement noise distribution of nonlinear state space models. The unknown noise distribution is modeled as a mixture of exponential family of distributions. We use the Expectation-Maximization (EM) method in order to jointly estimate the unknown parameters as well as the states. The online version of the EM algorithm is implemented by using particle filtering techniques. The resulting algorithm is a noise adaptive particle filter which is applicable to many sensor models having multi-modal noise distributions with unknown parameters.

In this study, we aim to estimate the unknown multi-modal measurement noise distribution of nonlinear state space models. The unknown noise distribution is modeled as a mixture of exponential family of distributions. We use the Expectation-Maximization (EM) method in order to jointly estimate the unknown parameters as well as the states. The online version of the EM algorithm is implemented by using particle filtering techniques. The resulting algorithm is a noise adaptive particle filter which is applicable to many sensor models having multi-modal noise distributions with unknown parameters.

In this study, we aim to estimate the unknown multi-modal measurement noise distribution of nonlinear state space models. The unknown noise distribution is modeled as a mixture of exponential family of distributions. We use the Expectation-Maximization (EM) method in order to jointly estimate the unknown parameters as well as the states. The online version of the EM algorithm is implemented by using particle filtering techniques. The resulting algorithm is a noise adaptive particle filter which is applicable to many sensor models having multi-modal noise distributions with unknown parameters.

This paper presents a novel power amplifier (PA) architecture based on the combination of radio frequency pulse width modulation (RFPWM) and multilevel PWM. The architecture provides better dynamic range at high carrier frequency compared to RFPWM. The benefits of this architecture over multilevel PWM are that it only requires a single PA and no combiner. The average efficiency for an 802.11g baseband signal is better than multilevel PWM. Our results also shows that the proposed technique exhibit a constant dynamic range at carrier frequency of 3, 4 and 5 GHz, in contrast to RFPWM which shows a decrease in dynamic range for increase in carrier frequency.

Implementation of wireless wideband transmitters using ΔΣ DACs requires very high speed modulators. Digital MASH ΔΣ modulators are good candidates for speed enhancement using interleaving because they require only adders and can be cascaded. This paper presents an analysis of the integrator critical path of two-channel interleaved ΔΣ modulators. The bottlenecks for a high-speed operation are identified and the performance of different logic styles is compared. Static combinational logic shows the best trade-off and potential for use in such high speed modulators. A prototype 12-bit second order MASH ΔΣ modulator designed in 65 nm CMOS technology based on this study achieves 9 GHz operation at 1 V supply.

Implementation of wireless wideband transmitters using ΔΣ DACs requires very high speed modulators. Digital MASH ΔΣ modulators are good candidates for speed enhancement using interleaving because they require only adders and can be cascaded. This paper presents an analysis of the integrator critical path of two-channel interleaved ΔΣ modulators. The bottlenecks for a high-speed operation are identified and the performance of different logic styles is compared. Static combinational logic shows the best trade-off and potential for use in such high speed modulators. A prototype 12-bit second order MASH ΔΣ modulator designed in 65 nm CMOS technology based on this study achieves 9 GHz operation at 1 V supply.

Implementation of wireless wideband transmitters using ΔΣ DACs requires very high speed modulators. Digital MASH ΔΣ modulators are good candidates for speed enhancement using interleaving because they require only adders and can be cascaded. This paper presents an analysis of the integrator critical path of two-channel interleaved ΔΣ modulators. The bottlenecks for a high-speed operation are identified and the performance of different logic styles is compared. Static combinational logic shows the best trade-off and potential for use in such high speed modulators. A prototype 12-bit second order MASH ΔΣ modulator designed in 65 nm CMOS technology based on this study achieves 9 GHz operation at 1 V supply.

Implementation of wireless wideband transmitters using ΔΣ DACs requires very high speed modulators. Digital MASH ΔΣ modulators are good candidates for speed enhancement using interleaving because they require only adders and can be cascaded. This paper presents an analysis of the integrator critical path of two-channel interleaved ΔΣ modulators. The bottlenecks for a high-speed operation are identified and the performance of different logic styles is compared. Static combinational logic shows the best trade-off and potential for use in such high speed modulators. A prototype 12-bit second order MASH ΔΣ modulator designed in 65 nm CMOS technology based on this study achieves 9 GHz operation at 1 V supply.

In this paper a technique suitable for on-chip IP3/IP2 RF test by embedded RF detectors is presented. A lack of spectral selectivity of the detectors and diverse nonlinearity of the circuit under test (CUT) impose stiff constraints on the respective test measurements for which focused calibration approach and a support by customized models of CUT is necessary. Also cancellation of second-order intermodulation effects produced by the detectors under the two-tone test is required. The test technique is introduced using a polynomial model of the CUT. Simulation example of a practical CMOS LNA under IP3/IP2 RF test with embedded RF detectors is presented showing a good measurement accuracy.

In this work gate bias cycled operation (GBCO) is used on a gas-sensitive SiC field effect transistor(“GasFET”) to increase the sensitivity and selectivity. Gate bias ramps introduce strong hysteresis in the sensor signal. The shape of this hysteresis is shown to be an appropriate feature both for the discrimination of various gases (NH3, CO, NO, CH4) and also different gas concentrations (250 and 500 ppm). The shape is very sensitive to ambient conditions. Thus, the influence of oxygen concentration and relative humidity as well as sensor temperature is investigated and reasons for the observed signal changes are discussed.

We investigate robust cooperative localization in LOS/NLOS environments in wireless sensor networks. Round-trip time-of-arrival signal metric is considered so that time synchronization among sensors can be avoided. Owing to the non-line-of-sight effect, we model the measurement error by a two-mode Gaussian mixture distribution. However, its parameters are assumed completely unknown. We propose a centralized localization algorithm, which jointly estimates the unknown geographical coordinates and the nuisance mixture model parameters. The expectation-maximization criterion is adopted here to implement the maximum likelihood estimator. In addition, we also compute the Cramér-Rao lower bound (CRLB) for our estimation problem and present the best achievable positioning accuracy in terms of the CRLB.

We investigate robust cooperative localization in LOS/NLOS environments in wireless sensor networks. Round-trip time-of-arrival signal metric is considered so that time synchronization among sensors can be avoided. Owing to the non-line-of-sight effect, we model the measurement error by a two-mode Gaussian mixture distribution. However, its parameters are assumed completely unknown. We propose a centralized localization algorithm, which jointly estimates the unknown geographical coordinates and the nuisance mixture model parameters. The expectation-maximization criterion is adopted here to implement the maximum likelihood estimator. In addition, we also compute the Cramér-Rao lower bound (CRLB) for our estimation problem and present the best achievable positioning accuracy in terms of the CRLB.

We investigate robust cooperative localization in LOS/NLOS environments in wireless sensor networks. Round-trip time-of-arrival signal metric is considered so that time synchronization among sensors can be avoided. Owing to the non-line-of-sight effect, we model the measurement error by a two-mode Gaussian mixture distribution. However, its parameters are assumed completely unknown. We propose a centralized localization algorithm, which jointly estimates the unknown geographical coordinates and the nuisance mixture model parameters. The expectation-maximization criterion is adopted here to implement the maximum likelihood estimator. In addition, we also compute the Cramér-Rao lower bound (CRLB) for our estimation problem and present the best achievable positioning accuracy in terms of the CRLB.

We investigate robust cooperative localization in LOS/NLOS environments in wireless sensor networks. Round-trip time-of-arrival signal metric is considered so that time synchronization among sensors can be avoided. Owing to the non-line-of-sight effect, we model the measurement error by a two-mode Gaussian mixture distribution. However, its parameters are assumed completely unknown. We propose a centralized localization algorithm, which jointly estimates the unknown geographical coordinates and the nuisance mixture model parameters. The expectation-maximization criterion is adopted here to implement the maximum likelihood estimator. In addition, we also compute the Cramér-Rao lower bound (CRLB) for our estimation problem and present the best achievable positioning accuracy in terms of the CRLB.

We investigate robust cooperative localization in LOS/NLOS environments in wireless sensor networks. Round-trip time-of-arrival signal metric is considered so that time synchronization among sensors can be avoided. Owing to the non-line-of-sight effect, we model the measurement error by a two-mode Gaussian mixture distribution. However, its parameters are assumed completely unknown. We propose a centralized localization algorithm, which jointly estimates the unknown geographical coordinates and the nuisance mixture model parameters. The expectation-maximization criterion is adopted here to implement the maximum likelihood estimator. In addition, we also compute the Cramér-Rao lower bound (CRLB) for our estimation problem and present the best achievable positioning accuracy in terms of the CRLB.

We study received signal strength-based cooperative localization in wireless sensor networks. We assume that the measurement noise fits a contaminated Gaussian model so as to take into account some outlier conditions. In addition, some environment-dependent parameters are assumed to be unknown. We propose an expectation-maximization based algorithm for robust centralized network localization without offline training. As benchmark for comparison, we express the best achievable localization accuracy in terms of the Cramér-Rao bound. Experimental results demonstrate the advantages of the proposed algorithm as compared to some representative algorithms.

We study received signal strength-based cooperative localization in wireless sensor networks. We assume that the measurement noise fits a contaminated Gaussian model so as to take into account some outlier conditions. In addition, some environment-dependent parameters are assumed to be unknown. We propose an expectation-maximization based algorithm for robust centralized network localization without offline training. As benchmark for comparison, we express the best achievable localization accuracy in terms of the Cramér-Rao bound. Experimental results demonstrate the advantages of the proposed algorithm as compared to some representative algorithms.

We study received signal strength-based cooperative localization in wireless sensor networks. We assume that the measurement noise fits a contaminated Gaussian model so as to take into account some outlier conditions. In addition, some environment-dependent parameters are assumed to be unknown. We propose an expectation-maximization based algorithm for robust centralized network localization without offline training. As benchmark for comparison, we express the best achievable localization accuracy in terms of the Cramér-Rao bound. Experimental results demonstrate the advantages of the proposed algorithm as compared to some representative algorithms.

We study received signal strength-based cooperative localization in wireless sensor networks. We assume that the measurement noise fits a contaminated Gaussian model so as to take into account some outlier conditions. In addition, some environment-dependent parameters are assumed to be unknown. We propose an expectation-maximization based algorithm for robust centralized network localization without offline training. As benchmark for comparison, we express the best achievable localization accuracy in terms of the Cramér-Rao bound. Experimental results demonstrate the advantages of the proposed algorithm as compared to some representative algorithms.

We study received signal strength-based cooperative localization in wireless sensor networks. We assume that the measurement noise fits a contaminated Gaussian model so as to take into account some outlier conditions. In addition, some environment-dependent parameters are assumed to be unknown. We propose an expectation-maximization based algorithm for robust centralized network localization without offline training. As benchmark for comparison, we express the best achievable localization accuracy in terms of the Cramér-Rao bound. Experimental results demonstrate the advantages of the proposed algorithm as compared to some representative algorithms.

We study received signal strength-based cooperative localization in wireless sensor networks. We assume that the measurement noise fits a contaminated Gaussian model so as to take into account some outlier conditions. In addition, some environment-dependent parameters are assumed to be unknown. We propose an expectation-maximization based algorithm for robust centralized network localization without offline training. As benchmark for comparison, we express the best achievable localization accuracy in terms of the Cramér-Rao bound. Experimental results demonstrate the advantages of the proposed algorithm as compared to some representative algorithms.

Visual tracking has attracted a significant attention in the last few decades. The recent surge in the number of publications on tracking-related problems have made it almost impossible to follow the developments in the field. One of the reasons is that there is a lack of commonly accepted annotated data-sets and standardized evaluation protocols that would allow objective comparison of different tracking methods. To address this issue, the Visual Object Tracking (VOT) workshop was organized in conjunction with ICCV2013. Researchers from academia as well as industry were invited to participate in the first VOT2013 challenge which aimed at single-object visual trackers that do not apply pre-learned models of object appearance (model-free). Presented here is the VOT2013 benchmark dataset for evaluation of single-object visual trackers as well as the results obtained by the trackers competing in the challenge. In contrast to related attempts in tracker benchmarking, the dataset is labeled per-frame by visual attributes that indicate occlusion, illumination change, motion change, size change and camera motion, offering a more systematic comparison of the trackers. Furthermore, we have designed an automated system for performing and evaluating the experiments. We present the evaluation protocol of the VOT2013 challenge and the results of a comparison of 27 trackers on the benchmark dataset. The dataset, the evaluation tools and the tracker rankings are publicly available from the challenge website(1).

Visual tracking has attracted a significant attention in the last few decades. The recent surge in the number of publications on tracking-related problems have made it almost impossible to follow the developments in the field. One of the reasons is that there is a lack of commonly accepted annotated data-sets and standardized evaluation protocols that would allow objective comparison of different tracking methods. To address this issue, the Visual Object Tracking (VOT) workshop was organized in conjunction with ICCV2013. Researchers from academia as well as industry were invited to participate in the first VOT2013 challenge which aimed at single-object visual trackers that do not apply pre-learned models of object appearance (model-free). Presented here is the VOT2013 benchmark dataset for evaluation of single-object visual trackers as well as the results obtained by the trackers competing in the challenge. In contrast to related attempts in tracker benchmarking, the dataset is labeled per-frame by visual attributes that indicate occlusion, illumination change, motion change, size change and camera motion, offering a more systematic comparison of the trackers. Furthermore, we have designed an automated system for performing and evaluating the experiments. We present the evaluation protocol of the VOT2013 challenge and the results of a comparison of 27 trackers on the benchmark dataset. The dataset, the evaluation tools and the tracker rankings are publicly available from the challenge website(1).

Visual tracking has attracted a significant attention in the last few decades. The recent surge in the number of publications on tracking-related problems have made it almost impossible to follow the developments in the field. One of the reasons is that there is a lack of commonly accepted annotated data-sets and standardized evaluation protocols that would allow objective comparison of different tracking methods. To address this issue, the Visual Object Tracking (VOT) workshop was organized in conjunction with ICCV2013. Researchers from academia as well as industry were invited to participate in the first VOT2013 challenge which aimed at single-object visual trackers that do not apply pre-learned models of object appearance (model-free). Presented here is the VOT2013 benchmark dataset for evaluation of single-object visual trackers as well as the results obtained by the trackers competing in the challenge. In contrast to related attempts in tracker benchmarking, the dataset is labeled per-frame by visual attributes that indicate occlusion, illumination change, motion change, size change and camera motion, offering a more systematic comparison of the trackers. Furthermore, we have designed an automated system for performing and evaluating the experiments. We present the evaluation protocol of the VOT2013 challenge and the results of a comparison of 27 trackers on the benchmark dataset. The dataset, the evaluation tools and the tracker rankings are publicly available from the challenge website(1).

Visual tracking has attracted a significant attention in the last few decades. The recent surge in the number of publications on tracking-related problems have made it almost impossible to follow the developments in the field. One of the reasons is that there is a lack of commonly accepted annotated data-sets and standardized evaluation protocols that would allow objective comparison of different tracking methods. To address this issue, the Visual Object Tracking (VOT) workshop was organized in conjunction with ICCV2013. Researchers from academia as well as industry were invited to participate in the first VOT2013 challenge which aimed at single-object visual trackers that do not apply pre-learned models of object appearance (model-free). Presented here is the VOT2013 benchmark dataset for evaluation of single-object visual trackers as well as the results obtained by the trackers competing in the challenge. In contrast to related attempts in tracker benchmarking, the dataset is labeled per-frame by visual attributes that indicate occlusion, illumination change, motion change, size change and camera motion, offering a more systematic comparison of the trackers. Furthermore, we have designed an automated system for performing and evaluating the experiments. We present the evaluation protocol of the VOT2013 challenge and the results of a comparison of 27 trackers on the benchmark dataset. The dataset, the evaluation tools and the tracker rankings are publicly available from the challenge website(1).

Visual tracking has attracted a significant attention in the last few decades. The recent surge in the number of publications on tracking-related problems have made it almost impossible to follow the developments in the field. One of the reasons is that there is a lack of commonly accepted annotated data-sets and standardized evaluation protocols that would allow objective comparison of different tracking methods. To address this issue, the Visual Object Tracking (VOT) workshop was organized in conjunction with ICCV2013. Researchers from academia as well as industry were invited to participate in the first VOT2013 challenge which aimed at single-object visual trackers that do not apply pre-learned models of object appearance (model-free). Presented here is the VOT2013 benchmark dataset for evaluation of single-object visual trackers as well as the results obtained by the trackers competing in the challenge. In contrast to related attempts in tracker benchmarking, the dataset is labeled per-frame by visual attributes that indicate occlusion, illumination change, motion change, size change and camera motion, offering a more systematic comparison of the trackers. Furthermore, we have designed an automated system for performing and evaluating the experiments. We present the evaluation protocol of the VOT2013 challenge and the results of a comparison of 27 trackers on the benchmark dataset. The dataset, the evaluation tools and the tracker rankings are publicly available from the challenge website(1).

This paper presents an extended target tracking method for tracking cars in urban traffic using data from laser range sensors. Results are presented for three real world datasets that contain multiple cars, occlusions, and maneuver changes. The cars shape is approximated by a rectangle, and single track steering models are used for the target kinematics. A multiple model approach is taken for both the dynamics modeling and the measurement modeling. A comparison to ground truth shows that the estimation errors are generally very small: on average the absolute error is less than half a degree for the heading. Multiple cars are handled using a multiple model PHD filter, where a variable probability of detection is integrated to enable tracking of occluded cars.

Optimal channel allocation is a key performance engineering aspect in single-carrier frequency-division multiple access (SC-FDMA). It is of significance to consider minimum sum power (Min-Power), subject to meeting specified users demand, since mobile users typically employ battery-powered handsets. In this paper, we prove that Min-Power is polynomial-time solvable for interleaved SC-FDMA (IFDMA). Then we propose a channel allocation algorithm for IFDMA, which is guaranteed to achieve global optimum in polynomial time. We numerically compare the proposed algorithm with optimal localized SC-FDMA (LFDMA) for Min-Power. The results show that LFDMA outperforms IFDMA in the maximal supported user demand. When the user demand can be satisfied in both LFDMA and IFDMA, LFDMA performs slightly better than IFDMA. However MinPower is polynomial-time solvable for IFDMA whereas it is not for LFDMA.

The spatial locations of transmitters play a cardinal role in evaluating the aggregate interference and hence the performance of large wireless networks. The most widely used approach for modeling the network geometry is the Poisson point process (PPP), mainly due to its analytical tractability. However, point process models with repulsion and inhibition, such as the Matern hardcore process, the Strauss process, the Ginibre point process, and the Poisson cluster process, are more accurate and realistic models than the PPP for actual heterogeneous cellular network (HetNets) deployments. Nevertheless, the limited analytical tractability of the aforementioned point processes makes it difficult or even impossible to obtain closed-form analytical expressions for network performance. In this paper, we provide a framework for approximating the interference distribution in wireless networks with spatial randomness. Specifically, the distribution of aggregate interference is approximated by known probability density functions, as a means to provide simple and tractable expressions for key performance metrics, i.e. coverage probability, area spectral efficiency, and average rate. We show the effectiveness of the proposed approach in analyzing large wireless networks with nodes exhibiting attraction and inhibition.

This paper analyzes the limits of FFT performance on FPGAs. For this purpose, a FFT generation tool has been developed. This tool is highly parameterizable and allows for generating FFTs with different FFT sizes and amount of parallelization. Experimental results for FFT sizes from 16 to 65536, and 4 to 64 parallel samples have been obtained. They show that even the largest FFT architectures fit well in today's FPGAs, achieving throughput rates from several GSamples/s to tens of GSamples/s.

This paper analyzes the limits of FFT performance on FPGAs. For this purpose, a FFT generation tool has been developed. This tool is highly parameterizable and allows for generating FFTs with different FFT sizes and amount of parallelization. Experimental results for FFT sizes from 16 to 65536, and 4 to 64 parallel samples have been obtained. They show that even the largest FFT architectures fit well in today's FPGAs, achieving throughput rates from several GSamples/s to tens of GSamples/s.

This paper analyzes the limits of FFT performance on FPGAs. For this purpose, a FFT generation tool has been developed. This tool is highly parameterizable and allows for generating FFTs with different FFT sizes and amount of parallelization. Experimental results for FFT sizes from 16 to 65536, and 4 to 64 parallel samples have been obtained. They show that even the largest FFT architectures fit well in today's FPGAs, achieving throughput rates from several GSamples/s to tens of GSamples/s.

This paper analyzes the limits of FFT performance on FPGAs. For this purpose, a FFT generation tool has been developed. This tool is highly parameterizable and allows for generating FFTs with different FFT sizes and amount of parallelization. Experimental results for FFT sizes from 16 to 65536, and 4 to 64 parallel samples have been obtained. They show that even the largest FFT architectures fit well in today's FPGAs, achieving throughput rates from several GSamples/s to tens of GSamples/s.

This paper analyzes the limits of FFT performance on FPGAs. For this purpose, a FFT generation tool has been developed. This tool is highly parameterizable and allows for generating FFTs with different FFT sizes and amount of parallelization. Experimental results for FFT sizes from 16 to 65536, and 4 to 64 parallel samples have been obtained. They show that even the largest FFT architectures fit well in today's FPGAs, achieving throughput rates from several GSamples/s to tens of GSamples/s.

Architecture on demand (AoD) node offers considerable flexibility against traditional ROADMs. The paper presents a cost-efficient network planning strategy that exploits the flexibility inherent in AoD. Results show that AoD can save significantly in node modules through a proper network design.

Current Mode Class-D Power Amplifiers (CMC-DPA) are attractive for fully integrated PA implementation as the output capacitance of the active device can be absorbed in the output matching network that can be realized with minimum number of components. This paper presents a simplified design approach for CMCD PA design using an integrated balun transformers. Also, expressions are derived for the optimum device sizing for second harmonic suppression resulting in improved efficiency. The amplifier is implemented in 130 nm CMOS process and encapsulated in QFN package. Measurement results show that the amplifier exhibits broadband response between 1.4 GHz and 2.1 GHz with peak output power of 26.8 dBm at 1.8 GHz using a 2.4 V supply. PAE remains above 40% for the entire range while peak PAE and drain efficiency are 45% and 48%, respectively.

The spectrum overcrowding drives investigating solutions to increase the usage of underutilized spectrum bands, minimize redundant interference and maximize expected throughput. Cognitive radio (CR) has presented itself as an appealing technology for solutions in energy constrained devices. Within this context, this paper introduces a system structure which enhances wireless multi-interfaced objects with cognitive radio. We propose a modular architecture to imbue such multi-interfaced devices with cognitive radio features, and based on it we present numerical results which identify performance boundaries and potential energy savings for an adaptive uncoded modulation scheme. Our results show that the tradeoff between throughput and energy consumption can be leveraged satisfactorily to enhance the lifetime significantly in noisy environments.